an analysis of the effect of distance learning on student

APPROVED: Johnetta Hudson, Major Professor Jim Laney, Committee Member Grant Simpson, Committee Member John Brooks, Program Coordinator John Stansell, Chair of the Department of

Teacher Education and Administration M. Jean Keller, Dean of College of Education Sandra L. Terrell, Dean of the Robert B.

Toulouse School of Graduate Studies

AN ANALYSIS OF THE EFFECT OF DISTANCE LEARNING SITE ON STUDENT

SELF-EFFICACY OF JUNIOR HIGH SCHOOL SPANISH STUDENTS

David W. Vroonland, B.A, M.E

Dissertation Prepared for the Degree of

DOCTOR OF EDUCATION

UNIVERSITY OF NORTH TEXAS

August 2004

Vroonland, David W., An analysis of the effect of distance learning on

student self-efficacy of junior high school Spanish students. Doctor of

Education (Education Administration), August 2004, 87 pp., 27 tables, 39 titles.

Prior to the development of interactive television, schools that were either

geographically isolated or financially restricted were often unable to provide

courses that may have been essential for students. Interactive television has

helped such school districts provide appropriate courses for their students.

Because student self-efficacy is a significant indicator of student success,

the relationship between distance learning and students’ self-efficacy requires

research. The problem of the study was to examine the impact of site location in

a distance learning environment on student self-efficacy in Spanish instruction.

The participants in this study were junior high school students enrolled in

distance-learning Spanish classes at two junior high schools in a north central

Texas independent school district. All of the students were taught by the same

instructor. The age range of the students was from 11 to 14 years of age, and all

students were in either the seventh or the eighth grade. Students took a

modified version of the Motivated Strategies for Learning Questionnaire at the

end of each treatment.

Using the counterbalanced design, each subject was matched to

themselves. In order to employ a counterbalanced design the researcher must

make certain that the number of groups used in the research equal the

number of treatments used. Using the counterbalanced design, the research can

compare the average performance of the groups for each treatment. T-tests for

nonindependent samples were used to compare the two treatments.

The findings indicate that there is no significant difference in the level of

student self-efficacy by site location. The findings in this study support the use of

distance learning as a medium for Spanish instruction at the junior high school

level. Because of the strong statistical relationship between self-efficacy and

student performance, teachers and administrators can reasonably believe that

site location will not hamper their students’ success.

ii

ACKNOWLEDGEMENTS

I would like to thank the superintendent, principals, and teacher in the

participating district. Without their approval and support this dissertation would

not have been possible. I would also like to thank the Texas Education Agency

for their help in finding data used in my dissertation.

The West Foundation was vital to my success in completing this dissertation.

I would like to thank them for their financial support of my doctoral studies. It was

because of the generosity of the West Foundation that I was able to afford the

cost of obtaining this degree, and for that I am very grateful.

Lastly I would like to thank my wife for her support of my efforts in putting

together this dissertation. From providing me quiet time away from the children,

to editing my work, and encouraging me through my efforts, my wife has been

my most important support for my completion of this degree.

iii

TABLE OF CONTENTS

Page

ACKNOWLEDGEMENTS ..............................................................................................ii

LIST OF TABLES.......................................................................................................... v

Chapter

1. INTRODUCTION ..................................................................................... 1

Rationale

Purpose

Statement of Problem

Research Questions

Definitions

Limitations/Delimitations

Summary

2. REVIEW OF RELATED LITERATURE 10

Introduction

Self-Efficacy Research

Measurement of Self-Efficacy

History of Distance Learning

Distance Learning Research

Summary

3. METHODOLOGY .................................................................................. 23

Introduction

Problem

Participants

Procedure

Design

Data Analysis

4. RESULTS .............................................................................................. 33

Introduction

iv

Findings

Summary

5. CONCLUSIONS AND RECOMMENDATIONS...................................... 43

Introduction

Conclusions

Summary of Results

Recommendations

APPENDICES ............................................................................................................. 54 LIST OF REFERENCES ............................................................................................. 81

v

LIST OF TABLES

Table Page

1 Diversity and Gender of Students 26

2 Total Number of Participants at Each Site by Minority and 26

Non-Minority Status

3 Total Number of Participants at Each Site by Gender Status 27

4 Total Number of Participants 27

5 Total Number of Participants by School 27

6 Total Number of Participants at Each Site 28

7 Results – All Students 37

8 Results – Males 38

9 Results – Females 39

10 Results – Non-Minority 40

11 Results – Minority 41

12 All Students: Control of Learning Beliefs 65

(t-test for Nonindependent Samples)

13 Outlier Removed – All Students: Control of Learning Beliefs 66


14 All Students: Self-Efficacy for Learning and Performance 67


vi

15 Outlier Removed – All Students: Self-Efficacy for Learning and 68

Performance (t-test for Nonindependent Samples)

16 Males: Control of Learning Beliefs 69


17 Outlier Removed – Males: Control of Learning Beliefs 70


18 Males: Self-Efficacy for Learning and Performance 71


19 Outlier Removed – Males: Self-Efficacy for Learning 72

and Performance (t-test for Nonindependent Samples)

20 Females: Control of Learning Beliefs 73


21 Females: Self-Efficacy for Learning and Performance 74


22 Non-Minority: Control of Learning Beliefs 75


23 Outlier Removed – Non-Minority: Control of Learning Beliefs 76


24 Non-Minority: Self-Efficacy for Learning and Performance 77


25 Outlier Removed – Non-Minority: Self-Efficacy for Learning 78

and Performance (t-test for Nonindependent Samples)

vii

26 Minority: Control of Learning Beliefs 79


27 Minority: Self-Efficacy for Learning and Performance 80


CHAPTER 1

INTRODUCTION

Introduction

For reasons ranging from students living a great distance from a university,

to personal time management needs, to limited local program offerings, a

demand was created for a nontraditional system of education. The system that

was created is commonly referred to as distance learning and began with

correspondence courses at the University of Chicago in 1892. In the 1920s

distance learning expanded to the use of radio, and then in the 1950s the system

was enhanced with the use of instructional television (Campbell, 1996) and a

variety of other tools ranging from telephones to audio tapes and various

combinations. While distance learning has been evolving over the years, it has

historically been used in the context of adult higher education, which is where the

focus of research has been. However, in the last few years, as the result of

technological innovation, limited public resources, and increased program

requirements, we are beginning to see the infiltration of this concept into the K-12

public schools.

With the evolutionary pinnacle of distance learning being the fairly recent

development of interactive television, new possibilities have arisen, especially for

the K-12 public school systems across the country. Prior to the development of

interactive television, schools that were either geographically isolated or

2

financially restricted were often unable to provide specialized courses, and in

some cases courses that may have been essential to students’ future success.

Recognizing that “educators have the responsibility to provide its users with the

resources they need to be productive and responsible citizens in a democratic

national and worldwide society,” (Riddle, 1994, p. 3) it is vital that schools be able

to offer to our students the essential courses, as determined by the curriculum.

With the technological innovation of interactive television, school districts

that previously could not afford or find the needed personnel for these classes

are now able to provide the educational opportunities once not available to their

students. Districts are beginning to “recognize that distance education with its

technological capabilities holds the promise of a solution” (Riddle, 1994, p. 1) in

K-12 public schools for providing educational opportunities that previously were

only available to students in school districts with the resources to find or afford

the needed personnel. For example, in Texas, according to the Texas Education

Agency’s Public Information Management System (PIEMS) data, the number of

districts in Texas reporting students using video conferencing for core academic

classes has jumped from just 31districts in 1998-1999 to 155 districts in 2002-

2003. This data also shows that the number of campuses has similarly jumped

from 33 campuses in 1998-1999 to 165 campuses in 2002-2003 (Gouge, 2004).

While using distance learning to provide the opportunities to students in

school districts that have been geographically isolated, or that are economically

struggling is promising for the students in America’s K-12 public schools, there

3

are concerns that need to be addressed. As has been done with traditional

school settings, research needs to be conducted in order to assure educators of

the viability of this new educational environment. From instructional methods to

psychological issues, we need to do all that we can to make sure that the

distance learning environment is the best possible educational environment we

can provide.

Rationale

One of the psychological constructs of interest to the researcher is that of

self-efficacy. Self-efficacy “reflects an individual’s confidence in his/her abilities

to perform the behavior required to produce specific outcomes (Kinzie, Delcourt

& Power, 1994, p. 747). Bandura (1994) asserts that “those who judge

themselves as inefficacious are more inclined to visualize failure scenarios that

undermine performance by dwelling on personal deficiencies and on how things

will go wrong” (p. 368). Considering these findings it becomes evident that as

educators we need to recognize the significant role that self-efficacy constructs,

such as outcome expectations, luck, effort, ability, and task difficulty play in the

success of our students.

Furthermore, research shows that academic self-efficacy beliefs are strongly

predictive of academic performance, (Pajares, 1995) and that a “student’s

perception of self can affect choice of activities, effort expended, and persistence

in the face of difficulties” (Schunk, 1983b, p. 512). This is significant because it

takes the psychological concept and constructs of self-efficacy and brings them

4

into the world of practice as related to education. For educators this should

increase the attention given to self-efficacy issues and alert us to the possible

impacts of educational initiatives and the effect these initiatives may have on

students’ self-efficacy.

Based on our understanding of students’ self-efficacy and the role it plays in

their academic success, it is essential to have confidence in the impact of new

practices on student self-efficacy. One of the new initiatives within the last five to

ten years has been the use of distance learning instructional settings to provide

instruction. This study will examine the impact of the two instructional sites

(receiving and sending) in a distance learning environment on the self-efficacy of

seventh grade students in Spanish classes. The hope is that, under existing

conditions in the distance learning classroom, no significant difference will be

found between the sending and receiving sites as it relates to a student’s self-

efficacy.

Purpose

In the present educational environment a significant focus is being placed on

multiple intelligence’s, student learning styles, brain research, and technology in

the K-12 public schools on student learning. While technology research exists

about teacher efficacy related to distance learning and technology, there is very

little research that explores the impact of site location in a distance learning

environment on student learning. In the distance learning environment (defined

as two-way video-conferencing), students are taught while at a site either with a

5

teacher present or at a distant site interacting with the teacher over a two-way

video-conferencing television. This process demands the attention of educators

as it pertains to student learning. The purpose of this study is to bridge a gap in

the research and to provide data that may prove useful to educators teaching in a

distance learning environment.

Because student self-efficacy has been shown to be a significant indicator of

student success in various classroom settings, the relationship between distance

learning and students’ self-efficacy is a topic that requires the attention of

research. Of particular interest to the researcher is the impact on students’ self-

efficacy in Spanish classes taught via distance education. This area is

interesting for the researcher because in Texas there is a supply and demand

problem related to the number of classroom teachers of Spanish.

According to the U.S. Department of Education Office of Federal Student

Aid, Texas schools have had a shortage of foreign language teachers since 1997

and the shortage continues through today. In response to this shortage,

administrators are turning more and more to distance education to fill the void.

While administrators are turning to distance learning to provide for classes like

Spanish, they are doing so out of necessity, not necessarily because they believe

it is the best way to educate children. While financially this may be feasible and

provide for personnel resources that might not otherwise be found, concerns over

impact on student performance need to be examined. The information from this

study may assist administrators as they determine how much focus and financial

6

support they should give to the continued development of distance education

courses in general, and more specifically, Spanish education in such an

instructional setting. It may also prove helpful to teachers who work in a distance

learning environment by providing them with information that may direct

psychological and educational methods employed.

While research has been done in traditional classroom settings on the

impact of various instructional methods on student self-efficacy, there has been

very little research examining the impact of a distance learning setting on the

self-efficacy of young students. Considering the importance of self-efficacy on

student performance, this void in the research needs to be filled. This study will

examine the impact of the different instructional settings in distance learning on

student self-efficacy. Through the examination of student self-efficacy in both the

sending and receiving sites of a distance learning setting the researcher hopes to

provide data that may shed light on the impact of instructional setting in a

distance learning environment on student self-efficacy.

Statement of Problem

The problem of the study was to examine the relationship that receiving

instruction in distance learning environment has with students’ self-efficacy

beliefs. Specifically, this study will examine the impact of site location in a

distance learning environment on student self-efficacy in Spanish instruction.

7

Research Questions

The research questions include:

1. Is there a significant difference in the self-efficacy of students receiving

instruction in Spanish via distance learning at the sending site versus receiving

site on the post-test measure of junior high school students’ self-efficacy?

2. Is there a significant difference in the self-efficacy of boys receiving instruction

in Spanish via distance learning at the sending site versus receiving site on the

post-test measure of junior high school students’ self-efficacy?

3. Is there a significant difference in the self-efficacy of girls receiving instruction

in Spanish via distance learning at the sending site versus receiving site on the

post-test measure of junior high school students’ self-efficacy?

4. Is there a significant difference in the self-efficacy of non-minority students

receiving instruction in Spanish via distance learning at the sending site versus

receiving site on the post-test measure of junior high school students’ self-

efficacy?

5. Is there a significant difference in the self-efficacy of minority students



efficacy?

Definitions

Self-efficacy: “Individuals’ beliefs about their capabilities to perform well on

events that affect their lives.” (Graham & Weiner, 1996)

8

Minority: Persons belonging to a racial grouping other than Anglo-American

Junior High: Students who are in the seventh or eighth grade

Distance Learning: Two-way video-conferencing classroom in which nearly half

of the student are receiving instruction face to face and the other half are

receiving instruction via the video-conferencing technology

Sending Site: The site in a distance learning class that has the instructor

physically present

Receiving Site: The site in a distance learning class that does not have the

instructor physically present

Limitations

One of the limitations of the study is that the findings cannot be generalized

to distance learning students outside of examined district. Further limitations

include the willingness of the students and faculty to participate in the study, the

students understanding of the questions as put forth in the survey of self-efficacy,

and that the survey for self-efficacy was not developed specifically for distance

learning.

Delimitation

Delimitations of the study include using only one teacher. This will be done

in order to eliminate teacher variables without having to use a large number of

teachers in the study. Another delimitation of the study is that only junior high

school students will be used because this is the area of interest to the

9

researcher. Finally, the study will examine only Spanish classes for distance

learning because this is the area that is commonly used in a distance learning

environment.

Summary

Distance learning has developed to the point that it is now a standard in our

K-12 public schools. Self-efficacy, a psychological construct that explains a

student’s belief about their ability to perform a specific task, has been shown in

many studies to be a strong predictor of student performance and persistence.

Self-efficacy research also indicates that students’ self-efficacy can be affected

by the environment, and various psychological and instructional techniques.

With this in mind, this study examined the effect of the distance learning site on

the self-efficacy of students. By examining the effect of the distance learning site

on the self-efficacy of students, I hope to present data that will help the principal

and teacher develop a distance learning environment that will optimize student

performance.

10

CHAPTER 2

REVIEW OF RELATED LITERATURE

Introduction

The educational environment provides a contextual influence on students’

self-efficacy, and some environments may not provide needed information to the

student and, therefore, the students’ level of self-efficacy may suffer (Schunk,

1985). While this has been understood by educators for years as it relates to a

traditional classroom setting, it has great meaning today within the context of

two-way video-conferencing classrooms. Students’ psychological states,

including self-efficacy, often have significant impacts on student motivation and

performance in school. Schunk (1985) asserts that “different psychological

procedures change behavior in part by creating and strengthening perceived self-

efficacy, which refers to personal judgments of one’s performance capabilities in

a given activity” (p. 4). Because self-efficacy can influence one’s choice of

activities, effort expended, and persistence in completing activities, “students

who have a low self-efficacy will tend to avoid certain activities, whereas those

who believe they are capable should participate more eagerly” (Schunk, 1988, p.

5). What can be found in the existing research is that students’ “self-efficacy

beliefs are important influences on motivation and behavior in part because they

mediate the relationship between knowledge and action” (Pajares, 1995, p. 4).

11

Thus, the willingness of an individual to engage in a task and put forth effort is

determined by their perception of their ability to perform the task.

Educators recognize that with the advent of the fairly new distance learning

environment of interactive television, there may be a solution to solving the

educational needs of the geographically-isolated and underserved populations of

our country (Riddle, 1994, p. 1-2). These telecommunication systems enable

educators to reach their goals of providing academic programs through the use

of technology and establishing new programs for students and citizens on a

statewide basis (Riddle, 1994). Distance learning is a very attractive means for

educators to fulfill their responsibility of providing their students with the

resources they need to become productive citizens, especially in underserved

geographic regions where the resources cannot be accessed in the traditional

manner. However, “upon establishing that there is value in providing education

to the previously underserved populations, and demonstrating that interactive

telecommunications systems provide a means to deliver that education, the next

task is to design those delivery systems so that students’ needs are met” (Riddle,

1994, p. 7). Of specific concern, considering the significance of self-efficacy on

student persistence and performance, should be the impact of this environment

on the self-efficacy perceptions of the students. In the literature review I will

examine research surrounding self-efficacy, self-efficacy measurement, the

history of distance learning, and distance learning.

12

Self-Efficacy

While the significance of motivation on student performance has been

evident to educators since the onset of public school education in America, until

recently it has not been the focus of significant research. In the 1950s, research

into student motivation began with Julian Rotter’s research into locus of control,

and later continued with the seminal research of Albert Bandura in the 1970s,

focusing on the role of self-efficacy in student motivation. Since then there has

been extensive research conducted on the way in which motivation influences

student behaviors and decisions.

In what is commonly known as social learning theory, Bandura (1977)

asserts that behaviors are learned through the continuous reciprocal interaction

of people, their environments and learning generated by previous experiences.

From this process individuals develop a sense of what they can accomplish, and

this influences future decisions based on efficacy expectations. Efficacy

expectations, or self-efficacy, “reflects an individual’s confidence in his/her

abilities to perform the behavior required to produce specific outcomes and is

thought to directly impact the choice to engage in a task, as well as the effort that

will be expended and the persistence that will be exhibited” (Kinzie, Delcourt &

Power, 1994, p. 747). Bandura (1996) also asserts that people’s belief in their

capabilities to exercise control over their level of functioning and environmental

demands will greatly affect their incentive to persist or even attempt a new goal.

This is significant because of the unique environmental demands presented by

13

distance learning. Bandura’s assertion requires a look at the potential impact of

this environment on student self-efficacy.

Bandura (1977) and Schunk (1985) have shown that student persistence is

impacted by efficacy expectations. For educators, the persistence that students

will exhibit in the face of difficulties is of great importance. Research in self-

efficacy has “revealed positive and statistically significant relationships between

self-efficacy beliefs and academic performance and persistence across a wide

variety of subjects” (Riddle, 1994, p. 54). Relative to this study, it has specifically

been found that a “student’s motivation to persist in a distance learning course is

more important in a distance learning telecourse than in a traditional classroom

course” (Campbell, 1996, p. 16). Persistence is significantly impacted when a

student believes that the environment in which they are learning is either

enhancing or inhibiting their ability or effort, or making the task more or less

difficult. Because of this, teachers need to have confidence that the environment

in which students learn will not negatively impact their student’s persistence.

Examining the relationship between the unique environmental demands of

distance learning and self-efficacy thus becomes vital.

Research has also focused on the relationship between the various

educational elements and a student’s self-efficacy. According to Pajares (1995),

researchers have studied, in an educational environment, the relationship

between self-efficacy and attributions, career development, goal setting, memory,

modeling, problem solving, reward contingencies, self-regulation, social

14

comparisons, strategy training, teaching and teacher education, anxiety and self-

concept, and academic performances across subject areas. In nearly all of this

research it has been found that self-efficacy is a strong predictor of academic

outcomes, and that “students’ self-efficacy can be influenced by such things as

prior performance, vicarious experiences, social persuasion, and inferences from

physiological states” (Schunk, 1984, p. 5).

Also of interest is a study conducted by Hagerty (1997) in which four schools

were selected as efficacy schools and over a period of two years academic

scores were compared with four non-efficacy schools. To qualify as an efficacy

school the teachers in the school had to partake in specific training provided by

the Efficacy Institute. This training “focused on improving the academic

performance of students through the development of positive attitudes toward

learning. This included a presentation of theory and discussion of such topics as

the innate ability and developmental models of learning as they operate at large

and in schools. The final day involved a developing of curriculum for students

based on what the teachers had learned in the training “(Hagerty, 1997, p. 1).

Four schools in the Sacramento City Unified School District completed the

training and were thus labeled efficacy schools. The comparison schools, whose

teachers had not gone through the training, were labeled non-efficacy schools.

Results indicated that in math, boys, African-American, and white student scores

improved more in the efficacy schools than the non-efficacy schools. This is

15

significant for educators because it provides concrete evidence of the important

role that self-efficacy plays in student academic performance.

Measurement of Self-Efficacy

While self-efficacy research has shown high predictability factors for student

performance, there has been concern that some of the research has been flawed

by the designs. Specifically, researchers such as Bandura, Bond, and Pajares

have had great concern over the manner in which self-efficacy has been

measured. Self-efficacy research should measure the confidence that students

have towards accomplishing a specific task in the future. The emphasis needs to

be on the specificity of the task. “Bandura cautioned that, because judgments of

self-efficacy are task- and domain-specific, global or inappropriately defined self-

efficacy assessments will weaken effects. For this reason, measures of self-

efficacy should be tailored to the criterial task being assessed” (Pajares, 1995, p.

6). Furthermore, “context-specificity is critical in self-efficacy assessment

because accurate judgments of one’s own capability toward tasks require all the

affordances and constraints of the task-performing situate be taken into

consideration” (Bong, 1999, p.1). Unfortunately, research frequently has focused

more on students’ general sense about their capability to perform well in a given

subject, as opposed to on a specific task. Therefore, what has often been the

topic of research in self-efficacy studies has more closely resembled a self-

concept construct. The difference between the two, while subtle, is significant.

Pajares (1995, p. 6) states “self-concept beliefs are generally defined in terms of

16

judgments of self-worth associated with one’s perceived competence”. Self-

efficacy, while it can be impacted by perceived competence, is less global in

nature and more specific to a given task. Therefore, while an individual’s overall

perception of self may be low, on a given task their efficacy perceptions may be

high, and vice versa.

In measuring self-efficacy it is important to keep the task specificity in mind

and develop a survey that is task specific. “Pajares and his associates showed

that, as Bandura theorized, particularized judgments of capabilities are better

predictors of highly related academic performances than more generalized self-

referent judgments” (Pajares, 1995, p. 21). Pajares’ (1995) research confirms

Bandura’s caution that a self-efficacy measure must assess the same skills

called for in the performance task with which it is to be compared. As important

in assessing self-efficacy is proximity of the assessment to the performance. To

ensure that self-efficacy is actually being measured, it is important that the

assessor measure self-efficacy in temporal proximity to the skill being examined

(Bong, 1999).

Self-efficacy measures, as pointed out early in this research, have been

shown to have significant predictability as it relates to student performance and

persistence, especially if the measurement is task specific and in close temporal

proximity to the action being measured. Within self-efficacy research, the most

common tool for conducting self-efficacy measurement is the Motivated

Strategies for Learning Questionnaire (MSLQ). Developed by the University of

17

Michigan to study motivation in college students, the MSLQ has been used in

motivation and self-efficacy research conducted with both junior high and high

school students. There are two sections to the MSLQ, but for the purposes of

this research only the section on motivation was used, which is appropriate since

the different scales can be used together or independently. Within the section on

motivation there are three subsections, of which the section dealing with

expectancy components was used in this research (Johnson and Ross, p. 4).

“The expectancy component assesses students’ control beliefs and sense of self-

efficacy for learning and performance” (Jans, p.8), which is the focus of this

study. Previous researchers have modified the questions in the MSLQ for the

purpose of readability, specificity of content, and to allow students to complete

the survey without teacher interaction. In each case the focus of the individual

questions was maintained, without changing the reliability and validity of the

survey.

History of Distance Learning

Recognizing the vital role of self-efficacy in student persistence and

performance, one would assume that innovations in public schools would

automatically receive the attention of research. As pointed out previously, self-

efficacy has been addressed in many different ways in the educational setting.

However, to date there has been very little research on the impact of distance

learning on self-efficacy in the K-12 public schools. For the purpose of this study,

I am defining distance learning as two-way audio-visual television.

18

With the advancement that has occurred in distance learning technology,

schools across the state of Texas have been implementing distance learning

classrooms at the cost of approximately $100,000 per permanently situated lab.

In the district in which this research was conducted five elementary schools

received labs in 2002, while each of the secondary campuses have had this

technology in place since 2000. Prior to the last five years, two-way interactive

audio-visual experiences have been primarily used by the military, businesses

and higher education. In public school settings this is a relatively new

technology, and very little research has been done to evaluate the instructional

effectiveness of this technology.

The nature and scope of distance education has changed radically since its

early beginnings as correspondence courses over 100 years ago (Campbell,

1996). While the first instructional television was introduced in 1951 (Lane,

1992), interactive television technology was still a long way off. Before the

introduction of such technology into our educational setting, Americans would still

have to go through multimedia education for distance learning, which

incorporated audio, video, and correspondence technology for the purpose of

relaying education information.

It was not until the mid 1980s that telecourses were offered for educational

opportunities, and since then the use of such technology has increased at a

staggering rate (Campbell, 1996). As noted earlier, in the state of Texas,

according to Public Education Information Management System (PIEMS) data

19

obtained from the Texas Education Agency, the number of districts in Texas

reporting students using video conferencing for core academic classes has

jumped from just 31districts in 1998-1999 to 155 districts in 2002-2003. The

number of campuses has similarly jumped from 33 campuses in 1998-1999 to

165 campuses in 2002-2003 (Gouge, 2004). The introduction of this technology

into the K-12 educational setting has removed significant barriers to equal

educational opportunities for students from geographically-isolated and

financially struggling communities, and indications are that nearly all states are

planning or implementing telecommunication systems for education (Riddle,

1994). However, “for most people, two-way audio/video distance education

environments are new experiences. New experiences by their nature can be

anxiety provoking” (Reinhart, & Schneider, 1998, p. 3). Couple this anxiety

related to technology with the new educational experience of Spanish for children

and you have the potential for even greater levels of anxiety.

Distance Learning Research

This anxiety has to be considered when evaluating the effectiveness of a

distance learning environment. While it has been established that distance

education can fill a significant void in educational opportunity for those who are

geographically-isolated and for financially strapped communities, there has been

little research into the impact of this delivery medium on K-12 students. The

significant amount of research conducted on distance learning has been primarily

reserved for the realm of higher education. Campbell (1996) pointed out

20

research conducted by Russel (1993) that indicated there was no significant

difference in the achievement of learning between students in traditional face-to-

face settings and those in distance learning settings. However, it is important to

note that this research focused on students in university settings, who had the

choice between the two environments, and not in a K-12 public school

environment where students generally do not get to determine the educational

setting. This is significant because many of the university students who make

the choice of a distance learning course would believe that they had the ability to

be successful in such a setting. Those who did not believe they could be

successful would not have attempted or persisted in such an environment.

Because of the nature of choice and the inherent relationship with self-efficacy,

much of the research on self-efficacy and distance learning may not be

generalizable to the K-12 public school system.

As referred to earlier, the U.S. Department of Education Office of Federal

Student Aid has found that Texas schools have had a shortage of foreign

language teachers since 1997 that continues through today. With an increased

need for Spanish instruction across the state of Texas and a decrease in the

number of qualified teachers, school administrators are turning more and more to

distance learning technology to fill the void. While “two-way audio-visual

distance education has the potential to provide real-time interaction, significant

impediments might result if the student is not comfortable with the technology”

(Reinhart, & Schneider, 1998, p. 4). Reinhart and Schneider (1998) also state

21

that a “students’ perception of the physical environment in a two-way audio/video

classroom will be related to their perceptions of self-efficacy in the classroom” (p.

4). Reinhart and Schneider’s research is significant to this present study

because it is one of the few that examines the relationship between the

environment of distance learning and self-efficacy. However, their research also

focused on college students whose level of self-efficacy may not match the whole

of students within a public school setting. Furthermore, while their research

looked at the effect of self-efficacy beliefs on student performance in a distance

learning environment, it did not evaluate the effect of the site location in a

distance learning environment on the student’s self-efficacy beliefs. Anderson

(1993), in a study of success in distance education telecourses versus traditional

classroom courses, concludes that motivation may be an important factor in the

successful persistence of students in distance education courses. While this is

consistent with prior self-efficacy research in traditional classroom settings, it is

important for K-12 institutions offering distance learning courses to know if the

findings of prior self-efficacy research based in traditional classrooms apply to

the distance learning setting. As Krendl and Broihier (1992) indicated, “as the

technology gains a stronger foothold on our educational institutions and becomes

a standard instructional tool in the classroom, as well as a fundamental

component of cultural literacy, it is critical that we understand students’ response

to this medium” (p. 225).

22

Summary

One solution to the problem of providing an adequate education to the

underserved and geographically isolated learner has been found in the electronic

telecommunications technologies (Riddle, 1994). With the support of the Texas

Legislature via Technology Infrastructure Grants, many Texas schools have

developed distance learning labs to bring educational opportunities that may not

have been possible before. This medium has increasingly been used to provide

courses for students that previously had not been offered because personnel

either could not be found or afforded. “While there are compelling reasons, e.g.,

cost effectiveness, marketing, and student access, for institutions to develop and

implement distance education programs, it is important to consider research as it

pertains to distance education” (Campbell, 1996. p. 2). This study examined

the impact of the distance learning site on student self-efficacy. The purpose of

this examination was to evaluate the relationship between the two variables to

establish the instructional effectiveness, as it relates to self-efficacy, of a distance

learning environment.

23

CHAPTER 3

METHODOLOGY

Introduction

This study examined the possible effect of site location in a distance learning

environment on the self-efficacy of junior high school students in Spanish

education.

The following research questions were addressed:


instruction in Spanish via distance learning at the sending site versus


efficacy?

2. Is there a significant difference in the self-efficacy of boys receiving



efficacy?

3. Is there a significant difference in the self-efficacy of girls receiving



efficacy?


receiving instruction in Spanish via distance learning at the sending site

24

versus receiving site on the post-test measure of junior high school

students’ self-efficacy?





Problem

Self-efficacy studies have shown, with a high degree of confidence, a

relationship between students’ levels of self-efficacy and future academic

performance. Assuming this relationship would continue within a distance

learning classroom, this study examined the effect of the students’ site position in

a distance learning classroom on their self-efficacy. The null hypothesis is that

the self-efficacy of students’ will not differ with any degree of significance based

upon the site position in a distance learning environment.

In this study I examined the relationship between self-efficacy and the site

position of students in a distance-learning course for Spanish instruction. While

there has been a significant amount of research on the effects of instructional

methods, and instructor influences on self-efficacy, there has been little research

on the effects of distance learning on students’ self-efficacy. The purpose of this

research is to fill in a gap in the existing research on self-efficacy and begin the

process of examining the various components of distance-learning and the

25

environmental impact on student learning, thus assisting administrators and

teachers in developing future distance-learning courses.

Participants

The participants in this study were junior high school students enrolled in

distance-learning Spanish classes at two junior high schools in a north central

Texas independent school district. All of the students were taught by the same

instructor, thus eliminating instructor variance. The age range of the students

was from 11 to 14 years of age, and all students were in either the seventh or the

eighth grade. There were twenty-nine total participants in the distance learning

class, with thirteen participants at School A and sixteen participants at School B.

At School A there were five male participants and eight female participants. Ten

of the participants at School A were non-minority, and three of the participants

were minority. At School B there were nine male participants and seven female

participants. Eight of the participants at School B were non-minority, and eight of

the participants were minority. The number of students for this study was

impacted by their willingness to participate. There were forty-nine students in the

two classes, but only twenty-nine decided to participate. This was due to either

the students desire not to participate, or their parent’s desire for them not to

participate.

26

Table 1

Diversity and Gender of Students

Student Group Student Numbers

School A

Boys 5

Girls 8

Minority 3

Non-Minority 10

School B

Boys 9

Girls 7

Minority 8

Non-Minority 8

Table 2

Total Number of Participants at Each Site by Minority and Non-Minority Status

Site Position

Sending Site Receiving Site

Minority n= 11 n= 11

Non-Minority n= 18 n= 18

27

Table 3

Total Number of Participants at Each Site by Gender Status

Site Position


Male n= 14 n= 14

Female n= 15 n= 15

Table 4

Total Number of Participants

Student Group Student Numbers

Boys 14

Girls 15

Minority 11

Non-Minority 18

Table 5 Total Number of Participants by School

School A School B

1st Two Weeks n= 13 n= 16

2nd Two Weeks n= 13 n= 16

28

Table 6

Total Number of Participants at Each Site


N= 29 N= 29

Permission to use these students in the study was obtained from the

University of North Texas Institutional Review Board, the participating schools

administration, the teacher, and the participating school district’s superintendent.

All students enrolled in the course needed written consent from parents in order

to participate in the study.

Instrumentation

Survey research was conducted at both School A and School B using the

Motivated Strategies for Learning Questionnaire (MSLQ) as a posttest measure

of self-efficacy. The MSLQ was developed at the University of Michigan in 1986

by Paul Pintrich, David Smith, Teresa Garcia, and Wilbert McKeachie. It has

been under development formally since 1986, and has been used extensively in

research on self-efficacy with populations ranging from junior high school

students to graduate level college students.

Procedures

Students at both sites were given a nine weeks grading period to acclimate

themselves to the technology used in a distance-learning environment. This was

done so that familiarity with technology or discomfort with technology could be

29

eliminated as a variable in the study. At the beginning of the study the instructor

taught from School A for a period of two weeks, using instructional techniques

that he had used prior to the beginning of the study so as to eliminate familiarity

with instructional method as a variable. Students in School B received the

instruction via distance learning technology from the same instructor and at the

same time as the students in School A. After two weeks, the instructor gave the

MSLQ to the students at the sending site (School A), and at the receiving site

(School B). Following this procedure, the instructor then repeated the same

steps teaching from School B, which then became the sending site, making

School A the receiving site.

These two schools have systemic differences in both social economic status

and ethnic breakdown. School A is a Title I school with a higher number and

percentage of minority and low social economic status students as compared to

School B, a non-Title I school. To control for the differences between the

populations of the two schools, a researcher can either use statistical or design

methods.

The analysis of covariance is the statistical method used “to control for initial

differences between groups before comparisons are made” (Gall, Borg, & Gall,

1996, p. 394). This is used because “the researcher cannot always select

comparison groups that are matched with respect to all relevant variables” (Gall,

Borg, & Gall, 1996, p. 395). Rather than controlling statistically, the researcher

can control by design. The means for controlling for confounding variables by

30

design is referred to as matching. “Matching is used to equate two groups on

one or more extraneous variable so that these extraneous variables do not

confound study of causal relationships involving the variables of primary interest

to the researcher” (Gall, Borg, & Gall, 1996, p. 387). Typically, matching involves

“recruiting a subject in the second group because he or she (or it) is a good

match for a particular subject in the first group” (Huck, 2000, p. 291) on

extraneous variables. Considering the social economic status and ethnic

differences between School A and School B, this type of matching would likely

result in the loss of African-American, Hispanic, and low social economic status

subjects from the study.

Since it is desirable to control for differences by design rather than

statistically, another matching design was employed. Using the counterbalanced

design, each subject was matched to themselves. In order to employ this design

“the number of groups must equal the number of treatments,” (Gay, 1992, p. 329)

which was the case in this study. Using this method, the “average performance

of the groups for each treatment can be compared” (Gay, 1992, p. 329). This is

what was done in this study, using t-test for nonindependent samples to compare

the two treatments. However, “a unique weakness of this design is potential

multiple-treatment interference that can result when the group receives more

than one treatment. Thus, a counterbalanced design should really only be used

when the treatments are such that exposure to one will not affect evaluation of

the effectiveness of another” (Gay, 1992, p. 330). In this study the students

31

exposure to distance learning via the sending site should not effect the

evaluation of their self-efficacy in the receiving site. By following this design the

group size at both the sending and receiving sites is doubled, making this study

more statistically robust. In addition, many extraneous variables are eliminated

because the two groups are identical.

Design

This research study is a quasi-experimental, counterbalanced, quantitative

design. Using a posttest measure of self-efficacy, comparative effects of sending

sites and receiving sites in distance-learning Spanish classes were examined for

race, gender and aggregate scores.

A two-tailed t-test for nonindependent samples was used to examine

differences between sending and receiving sites, both aggregate and

disaggregate (based on gender and minority status). A two-tailed t-test was used

as there is no assumption that the differences that may occur in the study will

occur in one direction. The t-test for nonindependent samples is being used,

because this is the type of test for significance that is used when the study

employs matching techniques. The formula for t-test for nonindependent

samples (Gay, 1992, p. 450) was used in a spreadsheet software product to test

the null hypothesis. An alpha level of .05 was used, as this is what most studies

use as a reasonable probability level.

32

Summary

The purpose of this study was to examine the possible effects of site position

in a distance-learning Spanish class consisting of junior high school students.

The interactions between site position and gender, and site position and race

were examined for the purpose of helping future administrators and teachers

design the most effective distance-learning environments possible.

33

CHAPTER 4

RESULTS

Introduction The purpose of this study was to examine the relationship that receiving

instruction in a distance learning environment has with students’ self-efficacy

beliefs. Specifically, this study examined the impact of site location in a distance

learning environment on student self-efficacy in Spanish instruction.

In this chapter the findings related to the research questions are presented.

Following the introduction the examination of the results are presented by

research question.

The questions for this research are as follows:




efficacy?




efficacy?


34



efficacy?









The instrument used in this research was the Motivated Strategies for

Learning Questionnaire (MSLQ). This instrument was developed at the

University of Michigan for the “purpose of assessing student motivational

orientations and their use of different learning strategies for a college course”

(Benson, 1991, p. 2). The MSLQ is divided into 15 scales that can be

administered as an entire instrument or used by subscales. For this study the

two subscales of the Expectancy Component under the Motivational Scales were

used, as these subscales relate to self-efficacy. The first subscale is titled

Control of Learning Beliefs (COLB), and the second is title Self-Efficacy for

Learning Performance (SLP). “The control of learning refers to students’ beliefs

35

that their efforts to learn will result in positive outcomes” (Pintrich et al., 1991, p.

12). The self-efficacy for learning and performance reflects the “judgment about

one’s ability to accomplish a task as well as one’s confidence in one’s skills to

perform that task” (Pintrich, et al., 1991, p. 13). The survey questions were

altered to meet the measurement specificity required for self-efficacy studies, and

to meet the language level of eleven to fourteen year old students. Questions 1,

4, 7, and 10 pertained to the Control of Learning Beliefs component. Questions

2, 3, 5, 6, 8, 9, 11, and 12 pertain to the Self-Efficacy for Learning and

Performance component. The following statements were used on the survey

instrument:

1. If I study in appropriate ways, then I will be able to speak using Spanish

food terms.

2. I believe I will receive an excellent grade in this class.

3. I’m certain I can understand the most difficult Spanish food terms from the

readings.

4. It is my own fault if I don’t learn the Spanish food terms in this unit.

5. I’m confident I can understand the basic Spanish food terms taught in this

unit.

6. I’m confident I can understand the most complex Spanish food terms

presented by the instructor in this unit.

36

7. If I try hard enough, then I will understand the material over Spanish food

terms.

8. I’m confident I can do an excellent job on the assignments and tests

covering Spanish food terms.

9. I expect to do well in this class.

10. If I don’t understand the Spanish food terms, it is because I didn’t try hard

enough.

11. I’m certain I can master the Spanish food terms being taught in this class.

12. Considering the difficulty of the material over Spanish food terms, the

teacher, and my skills, I think I will do well in this class.

Twenty-nine students completed questionnaires at the end of each two week

period of instruction. This number represents 59% of the students in the two

classes . Each student participated at both the receiving and sending sites.

There were eleven minority and eighteen non-minority students. There were

fourteen males and fifteen female students. The instructor confirmed that all

students understood the nature of the survey, that each student was in

attendance for entire period of the research, and that each student completed

their own survey without help.

A t-test for nonindependent samples was used, because this is the type of

test for significance that is used when research employs matching techniques.

Using the formula for t-test for nonindependent samples, students’ mean scores

37

at the sending site were compared with their mean scores at the receiving site to

come up with a t-test observed value to test for significance. The data revealed

that one student’s responses were dramatically different from all other student

responses. The difference in the data was the result of this student having a

larger disparity in survey responses between the sending and receiving sites in

comparison to other students. A note is at the end of the examination of results

for Questions 1, 2, and 4 sections to show the specific impact of including this

student’s scores. The following summarizes the results of the responses of the

29 students who completed the MSLQ successfully.

Examination of Results

Table 7

Results – All Students

Degrees of Freedom

t observed value Alpha t critical value

Control of Learning Beliefs

28 1.939558 .05 2.048

Self-Efficacy for Learning and Performance

28 1.694786 .05 2.048

Question 1: Is there a significant difference in the self-efficacy of students


38


efficacy?

As can be seen in Table 7, there is no significant difference in students’

beliefs about their ability to perform the given task in the future based upon

where the student is located in a two-way interactive television course. Neither

the COLB t observed values nor the SLP t observed values reached the level

required for there to be considered a statistically significant difference in

students’ self-efficacy at receiving and sending sites. Removing the outlier score

shows that the COLB t observed value for all students would have reduced to

1.632, and the SLP t observed value would have reduced to 1.350.

Table 8

Results – Boys

Degrees of Freedom



13 1.76453 .05 2.16


13 1.572676 .05 2.16

Question 2: Is there a significant difference in the self-efficacy of boys receiving



39

As can be seen in Table 8, there is no significant difference in boys’ beliefs

about their ability to perform the given task in the future based upon where the

boy is located in a two-way interactive television course. Neither the boys’ COLB

t observed value nor their SLP observed value reached the level required for

there to be considered a statistically significant difference in boys’ self-efficacy at

receiving and sending sites. Removing the outlier score shows that the COLB t

observed value for boys would have reduced to 1.440, and the SLP t observed

value would have reduced to 1.222.

Table 9

Results – Girls

Degrees of Freedom



14 .0863112 .05 2.145


14 .680864 .05 2.145

Question 3: Is there a significant difference in the self-efficacy of girls receiving



As can be seen in Table 9, there is no significant difference in girls’ beliefs

about their ability to perform the given task in the future based upon where the

40

girl is located in a two-way interactive television course. Neither the girls’ COLB t

observed value nor their SLP t observed value reached the level required for

there to be considered a statistically significant difference in girls’ self-efficacy at

receiving and sending sites.

Table 10

Results – Non-Minority

Degrees of Freedom



17 1.151394 .05 2.11


17 1.283717 .05 2.11

Question 4: Is there a significant difference in the self-efficacy of non-minority

students receiving instruction in Spanish via distance learning at the sending site

versus receiving site on the post-test measure of junior high school students’

self-efficacy?

As can be seen in Table 10, there is no significant difference in non-minority

students’ beliefs about their ability to perform the given task in the future based

upon where the non-minority student is located in a two-way interactive television

course. Neither the non-minority students’ COLB t observed values nor their

SLP t observed values reached the level required for there to be considered a

41

statistically significant difference in non-minority students’ self-efficacy at

receiving and sending sites. Removing the outlier score shows that the COLB t

observed value for non-minority students would have reduced to 0.558, and the

SLP t observed values would have reduced to 0.7667.

Table 11

Results – Minority

Degrees of Freedom



10 1.349627 .05 2.228


10 1.041566 .05 2.228

Question 5: Is there a significant difference in the self-efficacy of minority

students receiving instruction in Spanish via distance learning at the sending site

versus receiving site on the post-test measure of junior high school students’

self-efficacy?

As can be seen in Table 11, there is no significant difference in minority

students’ beliefs about their ability to perform the given task in the future based

upon where the minority student is located in a two-way interactive television

course. Neither the minority students’ COLB t observed value nor their SLP t

observed value reached the level required for there to be considered a

42

statistically significant difference in minority students’ self-efficacy at receiving

and sending sites.

Summary of Results

The findings by all students, as well as disaggregated by gender and race,

indicate that there is no significant difference in the level of student self-efficacy

by site location in a distance learning environment. A consideration of the outlier

data reveals that the scores would have been even further removed from the

point of significance.

43

CHAPTER 5

CONCLUSIONS AND RECOMMENDATIONS

Introduction

Distance learning, defined as two-way interactive television, has become a

means for districts across the state of Texas to meet the curriculum needs of

students. For districts that are experiencing economic problems or teacher

recruitment issues, the medium of interactive television is proving to be a

solution. According to the Texas Education Agency’s Public Information

Management System (PIEMS) data, the number of districts in Texas reporting

students using video conferencing for core academic classes has jumped from

just 31 districts in 1998-1999 to 155 districts in 2002-2003. This data also shows

that the number of campuses has similarly jumped from 33 campuses in 1998-

1999 to 165 campuses in 2002-2003 (Gouge, 2004). While using distance

learning to provide opportunities to students in school districts that are

experiencing teacher recruitment issues or that are economically struggling is

promising for the students in Texas K-12 public schools, there are concerns that

need to be addressed.

One of these concerns that needed to be addressed was this instructional

mediums impact on students’ self-efficacy, which is what this research set out to

do. Bandura (1994) asserts that “those who judge themselves as inefficacious

are more inclined to visualize failure scenarios that undermine performance by

44

dwelling on personal deficiencies and on how things will go wrong” (p. 368).

Furthermore, research shows that academic self-efficacy beliefs are strongly

predictive of academic performance (Pajares, 1995), and that a “student’s

perception of self can affect choice of activities, effort expended, and persistence

in the face of difficulties” (Schunk, 1983b, p. 512). This is significant because it

takes the psychological concept and constructs of self-efficacy and brings them

into the world of practice as related to education.

Bandura (1977) and Schunk (1985) have also shown that student

persistence is impacted by efficacy expectations. For educators, the persistence

that students will exhibit in the face of difficulties is of great importance.

Research in self-efficacy has “revealed positive and statistically significant

relationships between self-efficacy beliefs and academic performance and

persistence across a wide variety of subjects” (Riddle, 1994, p. 54). Relative to

this study, research has shown that a student’s motivation to persist in a course

is more important in a distance learning telecourse than in a traditional classroom

course (Campbell, 1996). Persistence is significantly impacted when a student

believes that the environment in which they are learning is either enhancing or

inhibiting their ability or effort, or making the task more or less difficult. Because

of this, teachers need to have confidence that the environment in which students

learn will not negatively impact their student’s persistence.

The importance of the impact of the environment on self-efficacy cannot be

minimized. In fact, Schunk (1985) found that the educational environment

45

provides a contextual influence on students’ self-efficacy, and some

environments may not provide needed information to the student and, therefore,

the students’ level of self-efficacy may suffer. Bandura’s (1996) research

supports Schunk’s statements in that he found that people’s belief in their

capabilities to exercise control over their level of functioning and environmental

demands will greatly affect their incentive to persist or even attempt a new goal.

These findings are significant to the purpose of this research because of the

unique environmental demands presented by distance learning.

The purpose of this study was to examine the relationship that receiving

instruction in a distance learning environment has with students’ self-efficacy

beliefs. Specifically, this study examined the impact of site location in a distance

learning environment on students’ self-efficacy in Spanish instruction. In this

chapter the conclusions from the findings related to the research questions are

presented. The questions for this research were as follows:




efficacy?




efficacy?

46




efficacy?









Data were collected using a modified version of the Motivated Strategies for

Learning Questionnaire (MSLQ) designed by the University of Michigan. Means

of student scores were then compared between sending and receiving sites to

determine if there were significant differences in student self-efficacy based on

site location in a distance learning environment.

Conclusions

The data indicate that students’ self-efficacy for the whole group did not

change significantly due to being located at the sending site versus being located

at the receiving site during instruction in a Spanish course. This outcome was

similarly reflected in the girls, boys, non-minority, and minority t-observed values.

47

As noted earlier, research has shown that self-efficacy plays an important role in

students’ choice of activities, as well as effort and persistence in activities

(Kinzie, Delcourt & Power, 1994). The fact that self-efficacy levels did not

significantly vary by site location indicates that students do not find the site

location in a distance learning environment to be a hindrance to their effort and

persistence in a Spanish course.

Reinhart and Schneider (1998) had noted that the new experience of

distance education could be anxiety provoking, which theoretically would impact

their level of self-efficacy. Through the design, the participants at both sites were

exposed to the technology for an extended period. This was done so that the

anxiety related to interfacing with new technology could be mostly eliminated.

Any remaining anxiety would mostly be related to the site location, as all other

variables were controlled. The data from this study indicate that any anxiety

experienced as a result of site location in a distance learning environment does

not negatively impact students’ level of self-efficacy.

Self-efficacy, as shown by Schunk (1984), Pajares (1995), and others, is

highly correlated to student performance. Research conducted by Russell (1993)

indicated there was no significant difference in the achievement of learning

between students in traditional face-to-face settings and those in distance

learning settings. I believed it was important to note that this research focused

on students in university settings, who had the choice between the two

environments, and not in a K-12 public school environment where students

48

generally do not get to determine the educational setting. However, the self-

efficacy findings in this study turned out to be consistent with Russell’s

conclusions, indicating that this environment is as appropriate to use with junior

high school students as with college age students.

The primary impetus for this study was determine if a distance learning

environment has an impact on student self-efficacy. Schunk (1985) concluded

that the educational environment does provide a contextual influence on

students’ self-efficacy, and some environments may not provide needed

information to the student and, therefore, the students’ level of self-efficacy may

suffer. Reinhart and Schneider’s research looked into Schunk’s conclusions as

they relate to a distance learning environment. Reinhart and Schneider (1998)

had concluded that students’ perception of the physical environment in a two-way

audio/video classroom was related to their perceptions of self-efficacy in the

classroom. Reinhart and Schneider’s research was significant to this study

because it is one of the few studies that examined the relationship between the

environment of distance learning and self-efficacy. However, their research

focused on college students, and once again, I was concerned that findings

involving college students’ would not be generalizable to students within a junior

high school. Furthermore, while their research looked at the relationship

between self-efficacy beliefs and a distance learning environment, it did not

evaluate the effect of the site location in a distance learning environment on the

student’s self-efficacy beliefs. These two studies supported the need to examine

49

the relationship between self-efficacy and site location in a junior high school

distance learning environment. The results of this study indicate that the

educational environment of distance learning does not negatively impact junior

high school students’ self-efficacy regardless of site location.

For the purposes of this research the examination of data involved looking at

comparisons self-efficacy scores within identified groups. The participants were

grouped by females, males, non-minorities and minorities. These groups were

examined independently and not compared to each other. The rationale behind

doing this was to exclusively examine the effective of site location on self-efficacy

for each group. The t-observed values that were obtained for each group

showed the statistical difference in self-efficacy between sending and receiving

sites in a distance learning environment, and were not a reflection of an overall

self-efficacy.

However, while the purpose of the study was not to compare one gender

group to another, when looking at the data it was interesting to note the

difference in the t-scores of the boys and the girls. In both the Control of

Learning Beliefs (COLB) and Self-Efficacy for Learning and Performance (SLP) t-

observed values the boys were noticeably closer to the t critical value and

showing a statistically significant difference between sending and receiving sites

than were the girls. Tables 8 and 9 in chapter 4 show that the girls’ t-observed

values were nearly half those of the boys. While neither the COLB nor SLP t-

observed values differences reached the t critical value, this difference in scores

50

led me to give an examination to prior research involving gender differences as it

relates to self-efficacy, and I found this difference in self-efficacy scores to be

consistent with prior research done by Pajares. Pajares (2002) found that

efficacy levels in middle school aged girls were higher than those of boys, and

especially so when the learning is more self-regulated.

From my observations and participations in a distance learning environment

I have found it to be an environment that requires a great deal of self-regulated

learning, especially at the receiving site. When examining the means, as shown

in tables 16, 18, 20, and 21 in Appendix C, I found the self-efficacy scores were

always lower at the receiving site for both genders, with a greater difference

among males. This is consistent with Pajares’ self-regulation findings in that the

receiving site in a distance learning environment would likely involve a greater

deal of self-regulation than the sending site, and thus I believe this to be a reason

for the differences in gender t observed values.

It is consistent with research to find that the difference in self-efficacy t-

scores could be due to girls’ efficacy levels being naturally higher than those of

boys. However, it is also consistent with research to find that this could be due to

the amount and type of self-regulated learning required in a distance learning

course.

Summary of Results

The null hypothesis in this study was that the self-efficacy of students will not

differ with any degree of significance based upon the site position in a distance

51

learning environment. While the findings in this study support the null

hypothesis, the results cannot be generally applied beyond the examined district

and Spanish instruction in a distance learning environment without further

research. This is due to the limitation of the study’s small sample size. The

number of participants was 29, which with the counterbalanced design gave a

number of 58, but the potential sample size was 49, which would have given a

number of 98. While this was a respectable acceptance rate of nearly 60%, I had

anticipated closer to an 80% acceptance rate. There were no complaints or

concerns reported by students or parents related to this study, which indicates

that they were not opposed to the study, but may have had other reason for not

participating that cannot be accounted for.

While the applicability to other districts is uncertain, the findings in this study

support the use of distance learning as a medium for Spanish instruction at the

junior high school level. The data show that self-efficacy of students, either as a

whole group, by gender, or by race was not impacted significantly by their

location in a distance learning environment. This is good news for those who

currently use or are planning to use distance learning as a means of instructing

students. Because of the strong statistical relationship between self-efficacy and

student performance, teachers can reasonably believe that their students will be

successful learning in a distance learning environment. While instructional

methods may need to vary from the traditional classroom due to the obvious

52

limitations of a two-way interactive television environment, student performance

need not suffer.

As noted earlier in the study, there is a shortage of Spanish teachers in the

state of Texas, and distance learning has been employed as an instructional

medium by an ever increasing number of districts to help overcome this

problem. Based on the findings in this research, school administrators concern

about the appropriateness of this medium for student learning can be somewhat

reduced. Furthermore, administrators can be that much more confident about

using taxpayer money in developing this medium for instruction. This can be

asserted because these findings demonstrate that student performance, as

indicated by self-efficacy measures, is not hampered by this environment.

Recommendations

While the results of this study provide support for distance learning, in order

for the results to be more generally applied across school districts, further

research will need to be conducted. Research recommendations would be to

replicate the study, but change some of the variables used in the study.

Specifically, increasing the time the teacher spent away from the receiving site

while providing instruction. In this study the teacher instructed from the sending

site to the receiving site for a two week period. It would be important to

practitioners to know if the students’ self-efficacy would be impacted by a greater

time separation in this environment, as it might impact the way in which their

courses were set up. A replication of this research using a greater number of

53

participants, different courses, and different teachers would help in determining if

the results of this study could be applied across different school settings.

One of the interesting findings of this study was the difference in the self-

efficacy t-scores between boys and girls in a distance learning environment.

While neither group’s t-scores differed with any degree of significance from the

sending and receiving sites in this environment, the difference between the

gender scores was noticeable. This research did not set out to examine the

amount or type of self-regulation in a distance learning environment, or to

compare gender groups. However, based upon the differences in the COLB and

SLP t observed values, I recommend further research into the amount and type

of self-regulated learning that potentially occurs in a distance learning

environment, and comparing gender group efficacy levels in this environment so

that educators can set up the most effective learning environment possible.

54

APPENDIX A

QUESTIONNAIRE

55

Self-Efficacy Survey Form

Student Number ____ Check the appropriate site location for the previous unit of instruction _____Sending Site _____Receiving Site The following questions ask about your motivation for and attitudes about this class. Remember there are no right or wrong answers, just answer as accurately as possible. Use the scale below to answer the questions. If you think the statement is very true of you, circle 7; if a statement is not at all true of you, circle 1. If the statement is more or less true of you, find the number between 1 and 7 that best describes you. 1 2 3 4 5 6 7

not at all very true true of me of me 1. If I study in appropriate ways, then I will be able 1 2 3 4 5 6 7 to speak using Spanish food terms. 2. I believe I will receive an excellent grade in this 1 2 3 4 5 6 7 class. 3. I’m certain I can understand the most difficult 1 2 3 4 5 6 7 Spanish food terms from the readings. 4. It is my own fault if I don’t learn the Spanish 1 2 3 4 5 6 7 food terms in this unit. 5. I’m confident I can understand the basic 1 2 3 4 5 6 7 Spanish food terms taught in this unit.

56

6. I’m confident I can understand the most complex 1 2 3 4 5 6 7 Spanish food terms presented by the instructor in this unit. 7. If I try hard enough, then I will understand the 1 2 3 4 5 6 7 material over Spanish food terms. 8. I’m confident I can do an excellent job on the 1 2 3 4 5 6 7 assignments and tests covering Spanish food terms. 9. I expect to do well in this class. 1 2 3 4 5 6 7 10. If I don’t understand the Spanish food terms, 1 2 3 4 5 6 7 it is because I didn’t try hard enough. 11. I’m certain I can master the Spanish 1 2 3 4 5 6 7 food terms being taught in this class. 12. Considering the difficulty of the material over 1 2 3 4 5 6 7 Spanish food terms, the teacher, and my skills,

I think I will do well in this class.

57

APPENDIX B

FORMS

58

Research by David Vroonland working with the University of North Texas

Denton, Texas

Student Assent Form **Required for students 7 -13 years old

Your Spanish teacher, (Teacher Name), with the permission of the

superintendent and principal, is assisting me in research. The research is about

how distance learning affects a student’s beliefs about how they will perform in

Spanish. The study will be during October and November of 2003. It will only be

conducted during class time, and should take approximately 30 minutes. The

purpose of this research is to give your teacher and others information that may

help them design better distance learning courses.

There will be no changes with the class beyond (Teacher Name) spending

approximately two weeks teaching from (School A), followed by two weeks

teaching from (School Name). You will be asked to fill out a survey at the end of

each unit. This survey has questions over students’ feelings about being able to

do what they learn in class. Your participation in this study is voluntary and not

related in any way to your grade in this class. You may withdraw from the study

at any time without hurting your grade. This research will not put you at any

expected risk or discomfort beyond what is normal in a school day.

To be a part of the research you must sign this Student Assent Form, and a

parent must sign the Parent Consent Form. There will be no negative results if

you do not want to participate. If you choose to participate, your identity will be

kept confidential by (Teacher Name).

This project has been reviewed and approved by the UNT Committee for the

Protection of Human Subjects (940-565-3940). Should you have questions

related to this study please feel free to call me, Dr. Johnetta Hudson (Faculty

59

Sponsor at UNT), the teacher, or your principal. I can be reached at 972-727-

0400 ext. 1242, and Dr. Hudson can be reached at 940-565-2175.

I have read or have had read to me all of the above. My Spanish teacher has

explained the study to me and answered all of my questions. I understand I do

not have to take part in this study and my refusal to participate or decision to

withdraw will involve no penalty. I understand my rights and voluntarily assent to

participate in this study. I understand what the study is about, how the study is

done, and why it is being done. I have been told I will receive a signed copy of

this Student Assent Form.


Denton, Texas

Student Assent Form **Required for students 7 -13 years old

________________________________ ________________________ Student Name (Please print) Date ________________________________ Signature of Student ________________________________ ________________________ Signature of Investigator Date

60


Denton, Texas

Parent Consent Form – Required if your child is from 7 to 13 years old Your child’s Spanish teacher, (Teacher Name), with the permission of the





purpose of this research is to give your child’s teacher and others information

that may help them design better distance learning courses.


approximately two weeks teaching from (School Name), followed by two weeks

teaching from (School Name). Your child will be asked to fill out a survey at the

end of each unit. This survey has questions over students’ feelings about being

able to do what they learn in class. Your child’s participation in this study is

voluntary and not related in any way to their grade in this class. Your child may

withdraw from the study at any time without hurting their grade. This research

will not put your child at any expected risk or discomfort beyond what is normal in

a school day.

In order for your child to be a part of the research you must sign this Parent

Consent Form and your child must sign the attached Student Assent Form.

There will be no negative results if your child does not want to participate. If your

child does participate, their identity will be kept confidential by (Teacher Name).




61



You are making a decision about whether or not to have your child participate in

this study. Your signature indicates that you have decided to allow your child to

participate, that you have read or have had read to you the information provided

in the Parent Consent Form, and you understand that you will receive a copy of

the signed Parent Consent Form and Student Assent Form.

Research by David Vroonland working with the

University of North Texas Denton, Texas

Parent Consent Form – Required if your child is from 7 to 13 years old

______________________________________ Student Name (Please print) ______________________________________ __________________ Parent Name (Please print) Date ______________________________________ Signature of Parent or Guardian (Only one parent or guardian signature is required) ___________________________________ ___________________ Signature of Investigator Date

62


Denton, Texas

Student Consent Form – For students 14 or older Your Spanish teacher, (Teacher Name), with the permission of the





purpose of this research is to give your teacher and others information that may

help them design better distance learning courses.


approximately two weeks teaching from (School Name), followed by two weeks

teaching from (School Name). You will be asked to complete a survey at the end

of each unit. This survey has questions over students’ feelings about being able

to do what they learn in class. Your participation in this study is voluntary and

not related in any way to your grade in this class. You may withdraw from the

study at any time without hurting your grade. This research will not put you at

any expected risk or discomfort beyond what is normal in a school day.

To be a part of the research you must sign this Student Consent Form. There

will be no negative results if you do not want to participate. If you choose to

participate, your identity will be kept confidential by (Teacher Name).






63

I have read or have had read to me all of the above. My Spanish teacher has

explained the study to me and answered all of my questions. I understand I do

not have to take part in this study and my refusal to participate or to decision to

withdraw will involve no penalty. I understand my rights and voluntarily consent

to participate in this study. I understand what the study is about, how the study is

done, and why it is being done. I have been told I will receive a signed copy of

this Student Consent Form.

Research by David Vroonland working with the

University of North Texas Denton, Texas

Student Consent Form – For students 14 or older

____________________________________ _____________________ Student Name (Please print) Date ____________________________________ Signature of Student _________________________________ _____________________ Signature of Investigator Date

64

APPENDIX C

DATA TABLES

65

Table 12 All Students: Control of Learning Beliefs (t-test for Nonindependent Samples)

Student Sending Receiving D D2 df t observed α t

critical 1 6.60 6.70 -0.10 0.01 28 1.939558 0.05 2.048 2 6.10 6.10 0.00 0.00 4 6.90 6.70 0.20 0.04 5 5.60 5.30 0.30 0.09 7 5.90 5.80 0.10 0.01 9 5.90 5.80 0.10 0.01 12 5.80 5.70 0.10 0.01 15 6.50 6.40 0.10 0.01 16 6.50 7.00 -0.50 0.25 19 5.50 5.70 -0.20 0.04 20 6.20 5.40 0.80 0.64 21 5.40 5.60 -0.20 0.04 23 6.80 6.80 0.00 0.00 24 4.10 3.90 0.20 0.04 25 3.30 2.70 0.60 0.36 26 7.00 7.00 0.00 0.00 27 6.10 5.90 0.20 0.04 28 6.50 4.70 1.80 3.24 30 5.10 4.50 0.60 0.36 32 5.90 5.20 0.70 0.49 34 5.57 5.90 -0.33 0.11 35 6.60 6.10 0.50 0.25 36 6.40 6.70 -0.30 0.09 37 6.00 6.40 -0.40 0.16 39 6.30 5.50 0.80 0.64 40 5.70 5.10 0.60 0.36 42 6.20 6.60 -0.40 0.16 44 4.80 4.80 0.00 0.00 47 5.90 6.10 -0.20 0.04 Average 5.90 5.73 Sum 5.07 7.49

66

Table 13 Outlier Removed - All Students: Control of Learning Beliefs (t-test for Nonindependent Samples)


critical 1 6.60 6.70 -0.10 0.01 28 1.632158 0.05 2.048 2 6.10 6.10 0.00 0.00 4 6.90 6.70 0.20 0.04 5 5.60 5.30 0.30 0.09 7 5.90 5.80 0.10 0.01 9 5.90 5.80 0.10 0.01 12 5.80 5.70 0.10 0.01 15 6.50 6.40 0.10 0.01 16 6.50 7.00 -0.50 0.25 19 5.50 5.70 -0.20 0.04 20 6.20 5.40 0.80 0.64 21 5.40 5.60 -0.20 0.04 23 6.80 6.80 0.00 0.00 24 4.10 3.90 0.20 0.04 25 3.30 2.70 0.60 0.36 26 7.00 7.00 0.00 0.00 27 6.10 5.90 0.20 0.04 30 5.10 4.50 0.60 0.36 32 5.90 5.20 0.70 0.49 34 5.57 5.90 -0.33 0.11 35 6.60 6.10 0.50 0.25 36 6.40 6.70 -0.30 0.09 37 6.00 6.40 -0.40 0.16 39 6.30 5.50 0.80 0.64 40 5.70 5.10 0.60 0.36 42 6.20 6.60 -0.40 0.16 44 4.80 4.80 0.00 0.00 47 5.90 6.10 -0.20 0.04 Average 5.88 5.76 Sum 3.27 4.25

67

Table 14 All Students: Self-Efficacy for Learning and Performance (t-test for Nonindependent Samples)


critical 1 6.55 6.73 -0.18 0.03 28 1.694786 0.05 2.048 2 6.09 6.09 0.00 0.00 4 6.91 6.73 0.18 0.03 5 5.73 5.55 0.18 0.03 7 5.82 5.64 0.18 0.03 9 5.91 5.82 0.09 0.01 12 5.82 5.91 -0.09 0.01 15 6.55 6.27 0.27 0.07 16 6.36 7.00 -0.64 0.40 19 5.55 5.45 0.09 0.01 20 6.00 5.36 0.64 0.40 21 5.64 5.91 -0.27 0.07 23 6.82 6.82 0.00 0.00 24 4.00 3.91 0.09 0.01 25 3.09 2.55 0.55 0.30 26 7.00 7.00 0.00 0.00 27 5.82 5.73 0.09 0.01 28 6.55 4.64 1.91 3.64 30 4.82 4.27 0.55 0.30 32 5.82 5.36 0.45 0.21 34 5.60 5.82 -0.22 0.05 35 6.64 6.09 0.55 0.30 36 6.45 6.55 -0.09 0.01 37 5.91 6.45 -0.55 0.30 39 6.18 5.55 0.64 0.40 40 5.82 5.45 0.36 0.13 42 6.27 6.64 -0.36 0.13 44 4.55 4.45 0.09 0.01 47 6.00 6.18 -0.18 0.03 Average 5.87 5.72 Sum 4.33 6.94

68

Table 15 Outlier Removed - All Students: Self-Efficacy for Learning and Performance (t-test for Nonindependent Samples)


critical 1 6.55 6.73 -0.18 0.03 28 1.350878 0.05 2.048 2 6.09 6.09 0.00 0.00 4 6.91 6.73 0.18 0.03 5 5.73 5.55 0.18 0.03 7 5.82 5.64 0.18 0.03 9 5.91 5.82 0.09 0.01 12 5.82 5.91 -0.09 0.01 15 6.55 6.27 0.27 0.07 16 6.36 7.00 -0.64 0.40 19 5.55 5.45 0.09 0.01 20 6.00 5.36 0.64 0.40 21 5.64 5.91 -0.27 0.07 23 6.82 6.82 0.00 0.00 24 4.00 3.91 0.09 0.01 25 3.09 2.55 0.55 0.30 26 7.00 7.00 0.00 0.00 27 5.82 5.73 0.09 0.01 30 4.82 4.27 0.55 0.30 32 5.82 5.36 0.45 0.21 34 5.60 5.82 -0.22 0.05 35 6.64 6.09 0.55 0.30 36 6.45 6.55 -0.09 0.01 37 5.91 6.45 -0.55 0.30 39 6.18 5.55 0.64 0.40 40 5.82 5.45 0.36 0.13 42 6.27 6.64 -0.36 0.13 44 4.55 4.45 0.09 0.01 47 6.00 6.18 -0.18 0.03 Average 5.85 5.76 Sum 2.42 3.30

69

Table 16 Males: Control of Learning Beliefs (t-test for Nonindependent Samples)


critical 2 6.10 6.10 0.00 0.00 13 1.76453 0.05 2.16 5 5.60 5.30 0.30 0.09 7 5.90 5.80 0.10 0.01 20 6.20 5.40 0.80 0.64 23 6.80 6.80 0.00 0.00 24 4.10 3.90 0.20 0.04 27 6.10 5.90 0.20 0.04 28 6.50 4.70 1.80 3.24 34 5.57 5.90 -0.33 0.11 35 6.60 6.10 0.50 0.25 37 6.00 6.40 -0.40 0.16 39 6.30 5.50 0.80 0.64 44 4.80 4.80 0.00 0.00 47 5.90 6.10 -0.20 0.04 Average 5.89 5.62 Sum 3.77 5.26

70

Table 17 Outlier Removed - Males: Control of Learning Beliefs (t-test for Nonindependent Samples)


critical 2 6.10 6.10 0.00 0.00 13 1.440026 0.05 2.16 5 5.60 5.30 0.30 0.09 7 5.90 5.80 0.10 0.01 20 6.20 5.40 0.80 0.64 23 6.80 6.80 0.00 0.00 24 4.10 3.90 0.20 0.04 27 6.10 5.90 0.20 0.04 34 5.57 5.90 -0.33 0.11 35 6.60 6.10 0.50 0.25 37 6.00 6.40 -0.40 0.16 39 6.30 5.50 0.80 0.64 44 4.80 4.80 0.00 0.00 47 5.90 6.10 -0.20 0.04 Average 5.84 5.69 Sum 1.97 2.02

71

Table 18 Males: Self-Efficacy for Learning and Performance (t-test for Nonindependent Samples)


critical 2 6.09 6.09 0.00 0.00 13 1.572676 0.05 2.16 5 5.73 5.55 0.18 0.03 7 5.82 5.64 0.18 0.03 20 6.00 5.36 0.64 0.40 23 6.82 6.82 0.00 0.00 24 4.00 3.91 0.09 0.01 27 5.82 5.73 0.09 0.01 28 6.55 4.64 1.91 3.64 34 5.60 5.82 -0.22 0.05 35 6.64 6.09 0.55 0.30 37 5.91 6.45 -0.55 0.30 39 6.18 5.55 0.64 0.40 44 4.55 4.45 0.09 0.01 47 6.00 6.18 -0.18 0.03 Average 5.84 5.59 Sum 3.42 5.22

72

Table 19 Outlier Removed - Males: Self-Efficacy for Learning and Performance (t-test for Nonindependent Samples)


critical 2 6.09 6.09 0.00 0.00 13 1.222981 0.05 2.16 5 5.73 5.55 0.18 0.03 7 5.82 5.64 0.18 0.03 20 6.00 5.36 0.64 0.40 23 6.82 6.82 0.00 0.00 24 4.00 3.91 0.09 0.01 27 5.82 5.73 0.09 0.01 34 5.60 5.82 -0.22 0.05 35 6.64 6.09 0.55 0.30 37 5.91 6.45 -0.55 0.30 39 6.18 5.55 0.64 0.40 44 4.55 4.45 0.09 0.01 47 6.00 6.18 -0.18 0.03 Average 5.78 5.66 Sum 1.51 1.58

73

Table 20 Females: Control of Learning Beliefs (t-test for Nonindependent Samples)


critical 1 6.60 6.70 -0.10 0.01 14 0.863112 0.05 2.145 4 6.90 6.70 0.20 0.04 9 5.90 5.80 0.10 0.01 12 5.80 5.70 0.10 0.01 15 6.50 6.40 0.10 0.01 16 6.50 7.00 -0.50 0.25 19 5.50 5.70 -0.20 0.04 21 5.40 5.60 -0.20 0.04 25 3.30 2.70 0.60 0.36 26 7.00 7.00 0.00 0.00 30 5.10 4.50 0.60 0.36 32 5.90 5.20 0.70 0.49 36 6.40 6.70 -0.30 0.09 40 5.70 5.10 0.60 0.36 42 6.20 6.60 -0.40 0.16 Average 5.91 5.83 Sum 1.30 2.23

74

Table 21 Females: Self-Efficacy for Learning and Performance (t-test for Nonindependent Samples)

Student Sending Receiving D D2 df t observed α t critical

1 6.55 6.73 -0.18 0.03 14 0.680864 0.05 2.145 4 6.91 6.73 0.18 0.03 9 5.91 5.82 0.09 0.01 12 5.82 5.91 -0.09 0.01 15 6.55 6.27 0.27 0.07 16 6.36 7.00 -0.64 0.40 19 5.55 5.45 0.09 0.01 21 5.64 5.91 -0.27 0.07 25 3.09 2.55 0.55 0.30 26 7.00 7.00 0.00 0.00 30 4.82 4.27 0.55 0.30 32 5.82 5.36 0.45 0.21 36 6.45 6.55 -0.09 0.01 40 5.82 5.45 0.36 0.13 42 6.27 6.64 -0.36 0.13 Average 5.90 5.84 Sum 0.91 1.72

75

Table 22 Non-Minority: Control of Learning Beliefs (t-test for Nonindependent Samples)


critical 1 6.60 6.70 -0.10 0.01 17 1.151394 0.05 2.11 2 6.10 6.10 0.00 0.00 4 6.90 6.70 0.20 0.04 5 5.60 5.80 -0.20 0.04 9 5.90 5.80 0.10 0.01 12 5.80 5.70 0.10 0.01 19 5.50 5.70 -0.20 0.04 20 6.20 5.40 0.80 0.64 21 5.40 5.60 -0.20 0.04 23 6.80 6.80 0.00 0.00 24 4.10 3.90 0.20 0.04 25 3.30 2.70 0.60 0.36 28 6.50 4.70 1.80 3.24 34 5.57 5.90 -0.33 0.11 35 6.60 6.10 0.50 0.25 36 6.40 6.70 -0.30 0.09 37 6.00 6.40 -0.40 0.16 44 4.80 4.80 0.00 0.00 Average 5.78 5.64 Sum 2.57 5.08

76

Table 23 Outlier Removed - Non-Minority: Control of Learning Beliefs (t-test for Nonindependent Samples)


critical 1 6.60 6.70 -0.10 0.01 17 0.55803 0.05 2.11 2 6.10 6.10 0.00 0.00 4 6.90 6.70 0.20 0.04 5 5.60 5.80 -0.20 0.04 9 5.90 5.80 0.10 0.01 12 5.80 5.70 0.10 0.01 19 5.50 5.70 -0.20 0.04 20 6.20 5.40 0.80 0.64 21 5.40 5.60 -0.20 0.04 23 6.80 6.80 0.00 0.00 24 4.10 3.90 0.20 0.04 25 3.30 2.70 0.60 0.36 34 5.57 5.90 -0.33 0.11 35 6.60 6.10 0.50 0.25 36 6.40 6.70 -0.30 0.09 37 6.00 6.40 -0.40 0.16 44 4.80 4.80 0.00 0.00 Average 5.74 5.69 Sum 0.77 1.84

77

Table 24 Non-Minority: Self-Efficacy for Learning and Performance (t-test for Nonindependent Samples)


critical 1 6.55 6.73 -0.18 0.03 17 1.283717 0.05 2.11 2 6.09 6.09 0.00 0.00 4 6.91 6.73 0.18 0.03 5 5.73 5.64 0.09 0.01 9 5.91 5.82 0.09 0.01 12 5.82 5.91 -0.09 0.01 19 5.55 5.45 0.09 0.01 20 6.00 5.36 0.64 0.40 21 5.64 5.91 -0.27 0.07 23 6.82 6.82 0.00 0.00 24 4.00 3.91 0.09 0.01 25 3.09 2.55 0.55 0.30 28 6.55 4.64 1.91 3.64 34 5.60 5.82 -0.22 0.05 35 6.64 6.09 0.55 0.30 36 6.45 6.55 -0.09 0.01 37 5.91 6.45 -0.55 0.30 44 4.55 4.45 0.09 0.01 Average 5.77 5.61 Sum 2.87 5.19

78

Table 25 Outlier Removed - Non-Minority: Self-Efficacy for Learning and Performance (t-test for Nonindependent Samples)


critical 1 6.55 6.73 -0.18 0.03 17 0.766715 0.05 2.11 2 6.09 6.09 0.00 0.00 4 6.91 6.73 0.18 0.03 5 5.73 5.64 0.09 0.01 9 5.91 5.82 0.09 0.01 12 5.82 5.91 -0.09 0.01 19 5.55 5.45 0.09 0.01 20 6.00 5.36 0.64 0.40 21 5.64 5.91 -0.27 0.07 23 6.82 6.82 0.00 0.00 24 4.00 3.91 0.09 0.01 25 3.09 2.55 0.55 0.30 34 5.60 5.82 -0.22 0.05 35 6.64 6.09 0.55 0.30 36 6.45 6.55 -0.09 0.01 37 5.91 6.45 -0.55 0.30 44 4.55 4.45 0.09 0.01 Average 5.72 5.66 Sum 0.96 1.54

79

Table 26 Minority: Control of Learning Beliefs (t-test for Nonindependent Samples)


critical 7 5.90 5.80 0.10 0.01 10 1.349627 0.05 2.228 15 6.50 6.40 0.10 0.01 16 6.50 7.00 -0.50 0.25 26 7.00 7.00 0.00 0.00 27 6.10 5.90 0.20 0.04 30 5.10 4.50 0.60 0.36 32 5.90 5.20 0.70 0.49 39 6.30 5.50 0.80 0.64 40 5.70 5.10 0.60 0.36 42 6.20 6.60 -0.40 0.16 47 5.90 6.10 -0.20 0.04 Average 6.10 5.92 Sum 2.00 2.36

80

Table 27 Minority: Self-Efficacy for Learning and Performance (t-test for Nonindependent Samples)


critical 7 5.82 5.64 0.18 0.03 10 1.041566 0.05 2.228 15 6.55 6.27 0.27 0.07 16 6.36 7.00 -0.64 0.40 26 7.00 7.00 0.00 0.00 27 5.82 5.73 0.09 0.01 30 4.82 4.27 0.55 0.30 32 5.82 5.36 0.45 0.21 39 6.18 5.55 0.64 0.40 40 5.82 5.45 0.36 0.13 42 6.27 6.64 -0.36 0.13 47 6.00 6.18 -0.18 0.03 Average 6.04 5.92 Sum 1.36 1.73

81

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